Data Governance Lead

SUMMARY:
Data Governance Lead (12-Month Contract)
Gijima Staffing Solutions is recruiting on behalf of a client for an experienced Data Governance Lead to establish and drive enterprise-wide data governance practices across a large, complex organisation. This is an exciting opportunity for a strategic data governance professional to lead the development of governance frameworks, improve data quality, and enable trusted, compliant, and AI-ready data across the business.
Location: Centurion (Hybrid – Remote Working)
Contract Duration: 12 Months (3-month probation)
Closing Date: 30 July 2026

POSITION INFO:
Purpose of the Role
The Data Governance Lead will be responsible for establishing, embedding, and continuously maturing the organisation's enterprise data governance framework, operating model, policies, controls, stewardship practices, and performance measures required to manage data as a strategic business asset.
The successful candidate will drive improvements in data quality, accountability, transparency, compliance, and decision-making across operational, technical, and corporate data domains. As the organisation expands its use of Artificial Intelligence (AI), this role will also lead governance for AI-related data risks, including training data provenance, model input and output quality, algorithmic transparency, and responsible AI compliance.

Minimum Qualifications

• Bachelor's Degree (NQF Level 7) in a relevant field (essential)
• Postgraduate qualification in Data Management, Information Systems, or Business Administration (advantageous)
• Certified Data Management Professional (CDMP) Practitioner or Master level, or currently working towards certification (highly advantageous)
• Exposure to AI governance frameworks or Responsible AI standards such as ISO/IEC 42001 or the NIST AI Risk Management Framework will be advantageous

• 8–10 years' experience in Data Management, Business Intelligence, or Enterprise Data Management
• At least 5 years leading enterprise Data Governance, Data Quality, Master Data, or Data Stewardship initiatives within large organisations
• Demonstrated experience implementing enterprise Data Governance frameworks in complex environments
• Experience establishing governance operating models, governance forums, policies, controls, and adoption roadmaps
• Exposure to governing data for AI and advanced analytics initiatives will be advantageous
• Proven ability to engage and influence senior stakeholders across business, IT, Risk, Audit, and Compliance
• Experience within the mining or heavy industrial sector will be a strong advantage
• Working knowledge of POPIA and other relevant data privacy and regulatory frameworks

• Strong knowledge of DAMA-DMBOK2 principles including:
• Data Governance
• Data Quality
• Metadata Management
• Master Data Management
• Data Architecture
• Experience with enterprise BI and data platforms including SAP BW/4HANA, SAP HANA, BusinessObjects, Tableau, and AWS Data Lake
• Knowledge of metadata management, data cataloguing, lineage, and data quality platforms
• Understanding of enterprise data architecture and governance best practices
• Knowledge of AI/ML data lifecycle concepts including model inputs, training data, model drift, explainability, and bias
• Awareness of AI governance frameworks including ISO/IEC 42001, the EU AI Act, and the NIST AI Risk Management Framework
• Understanding of mining value chain data will be advantageous

• Designing, implementing, and continuously improving the enterprise Data Governance Framework
• Developing governance policies, standards, procedures, and controls covering data quality, metadata, master data, privacy, classification, and lifecycle management
• Establishing governance councils, forums, operating models, and stewardship communities
• Defining and implementing enterprise Data Quality standards, Critical Data Elements (CDEs), scorecards, and remediation processes
• Leading Metadata Management, Business Glossary, Data Catalogue, and Data Lineage initiatives
• Driving Master Data Governance across key business domains
• Ensuring compliance with POPIA, legal retention requirements, records management standards, and corporate governance obligations
• Managing enterprise Data Risk registers, governance controls, audit readiness, and remediation activities
• Extending governance practices to support Artificial Intelligence, Machine Learning, predictive analytics, and advanced analytics initiatives
• Establishing governance requirements for AI training data, model documentation, monitoring, transparency, and responsible AI practices
• Partnering with business leaders, IT, Information Security, Legal, Risk, and Data Engineering teams to embed governance across the organisation
• Driving organisational adoption through stakeholder engagement, communication, awareness programmes, and training initiatives

• Strategic and enterprise-wide thinking
• Strong stakeholder engagement and influencing skills
• Excellent communication and facilitation abilities
• Analytical problem-solving capability
• Strong governance, compliance, and risk management mindset
• High attention to detail and commitment to data quality
• Ability to drive organisational change and continuous improvement
• Professional integrity and sound judgement when handling sensitive information